import numpy as np
import mxnet as mx
from mxnet import nd
import snlay as snlay


def mxmod_arr_loss(x, target, mxmodel):
    x_np = np.array(x)
    x_np = (x_np - 50.0)/20.0
    res2 = mxmodel.predict(x_np)
    y_t = nd.array(target, ctx=mx.gpu())
    err = nd.abs(y_t - res2)/y_t
    err2 = 100*nd.mean(err, axis=1).asnumpy()
    return err2


def loss_func(x, target, mats, lams):
    spec_ac = snlay.calc_spectrum(x, mats, lams)
    diff = np.abs(target - spec_ac)/target
    return 100*np.amax(diff)